• Asian Journal of Innovation and Policy
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• 제7권2호
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• pp.310-337
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• 2018

Adoption of mobile learning (m-learning) is not new in Malaysian oil and gas industry, with heavy investment into research and development to train the workers. Nevertheless, the low application of learnt skills on the job remains an emergent research area where there is a missing link on the effects of m-learning and effective organisational learning and implication on its training transfer. The result of this quantitative research revealed that all variables in m-learning were found to have a positive relationship with the effective organisational learning, and there is evidence of training transfer as a mediator of the relationship between self-directed learning, training design, work environment and effective organisational learning. However, there were some discrepancies in the extend of training transfer between trainee characteristics and organisational learning. As such, some important issues emerged which challenge the importance of evaluating workers' readiness and transfer for a successful implementation of m-learning towards developing effective organisational learning.

• 한국콘텐츠학회논문지
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• 제12권4호
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• pp.263-272
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• 2012

본 연구는 공무원 교육훈련정책의 상대적 중요도와 우선순위 분석을 통해 공무원교육훈련정책의 방향성을 모색해보고자 전문가들을 대상으로 AHP 방법론을 적용한 실증적 분석을 실시하였다. 연구결과를 요약해 보면 다음과 같다. 첫째, 측정영역별 평가요소에 대한 상대적 우선순위를 보면, 교육훈련운영시스템, 교육훈련프로그램, 교육인프라, 교육훈련평가관리 중에서 교육훈련운영시스템이 가장 중요한 평가요소로 분석되었다. 둘째, 평가항목의 관점에서 보면, 교육훈련프로그램에서는 Acting Learning 교육프로그램, 교육훈련운영시스템에서는 교육훈련기관 예산확충, 교육훈련평가관리에서는 교육훈련과 인사제도 연계, 교육인프라에서는 교수요원 확보 등이 상대적으로 가장 중요한 우선순위로 평가되었다. 이러한 분석결과는 공무원 교육훈련정책을 경험적으로 설명하는데 기여할 것으로 판단된다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.137-145
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• 2020

Providing safety training to construction workers is essential to reduce safety accidents at the construction site. With the prosperity of visualization technologies, Immersive Virtual Reality (IVR) has been adopted for construction safety training by providing interactive learning experiences in a virtual environment. Previous research efforts on IVR-based training have found that the level of fidelity of interaction between real and virtual worlds is one of the important factors contributing to the sense of presence that would affect training performance. Various interactive devices that link activities between real and virtual worlds have been applied in IVR-based training, ranging from existing computer input devices (e.g., keyboard, mouse, joystick, etc.) to specially designed devices such as high-end VR simulators. However, the need for high-fidelity interactive devices may hinder the applicability of IVR-based training as they would be more expensive than IVR headsets. In this regard, this study aims to understand the impact of the level of fidelity of interactive devices in the sense of presence in a virtual environment and the training performance during IVR-based forklift safety training. We conducted a comparative study by recruiting sixty participants, splitting them into two groups, and then providing different interactive devices such as a keyboard for a low fidelity group and a steering wheel and pedals for a high-fidelity group. The results showed that there was no significant difference between the two groups in terms of the sense of presence and task performance. These results indicate that the use of low-fidelity interactive devices would be acceptable for IVR-based safety training as safety training focuses on delivering safety knowledge, and thus would be different from skill transferring training that may need more realistic interaction between real and virtual worlds.

• 한국화재소방학회논문지
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• 제21권3호
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• pp.104-112
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• 2007

교육, 훈련, 연구에 사용된 의료 시뮬레이션 교육으로서 마네킹 시뮬레이터(mannequin simulator)의 개발은 오랜 시간에 걸쳐 이루어지고 있으며, 심폐소생술, 심장 수술, 마취 임상 수기, 위기관리(crisis management)에 대한 효율성 평가로 이어졌다. 최근 한국의 여러 의과대학에서 시뮬레이션 교육을 도입하여 임상 수기 교육을 하고 있으며, 시뮬레이션 센터를 설립하고 있다. 선진국의 응급의학분야에서 응급구조사의 역할이 매우 중요하게 대두되고 있으며, 한국에서 응급구조사의 효율적인 교육과 역할 수행을 위해 마네킹 시뮬레이터를 이용한 교육이 매우 중요하다. 본 연구는 이러한 의학 분야 시뮬레이션이 의과대학 교육뿐 아니라 구조구급 분야에 종사하는 소방공무원, 간호사, 응급구조사 양성 교육 등 의료의 여러 영역에서 다양하게 이용되는 의료시뮬레이션 진화와 교육에 대해 소개하고자 한다.

• International Journal of Quality Innovation
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• 제7권1호
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• pp.195-205
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• 2006

Both the total quality management (TQM) and learning organization (LO) appear to be promising approaches for organizational transformation towards a more effective, efficient, and responsive organization in the past. The evolutionary development and theory supports for these two fields are distinct but they appear to have more in common than they have in distinctiveness. However, there is little synergy developed between these two fields both in academic research and industrial applications. It is possibly due to the fact that both the academia and industry are taking a limiting polarized view of TQM and LO and hence not getting the benefits of linking the two. This paper tries to establish a link between the organizational learning capability and the quality culture for TQM implementation based on a case study on the largest vocational education institution, the Vocational Training Council, of Hong Kong. The study reveals that there is a strong positive correlation between organizational learning capability and quality culture. The exploratory explanations for the links between the organizational learning capability constructs and the quality culture constructs are also discussed in this paper. The findings of the study support other literatures that TQM should be embedded in LO and serves as an enabler for organizational learning (OL) in transforming and creating organizations which continuously expand their abilities to change and shape their future.

• KDI Journal of Economic Policy
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• 제44권2호
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• pp.29-44
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• 2022

This study compares the wage equation in Korea to those in other countries, focusing on the wage returns to adult education and training (AET) participation. It is found that the wage compensation structure in Korea is associated mainly with job characteristics such as tenure and workplace size rather than with worker characteristics such as AET participation and cognitive abilities. It is also found that Korea's AET participation is skewed toward non-job-related AET, relative to the situations in other countries. These findings imply that the link between a worker's productivity and wage should be strengthened in order to incentivize workers to invest in AET relevant to the labor market.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.192-198
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• 2024

This paper investigates the application of multi-agent deep reinforcement learning in the fighting game Samurai Shodown using Proximal Policy Optimization (PPO) and Advantage Actor-Critic (A2C) algorithms. Initially, agents are trained separately for 200,000 timesteps using Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP) with LSTM networks. PPO demonstrates superior performance early on with stable policy updates, while A2C shows better adaptation and higher rewards over extended training periods, culminating in A2C outperforming PPO after 1,000,000 timesteps. These findings highlight PPO's effectiveness for short-term training and A2C's advantages in long-term learning scenarios, emphasizing the importance of algorithm selection based on training duration and task complexity. The code can be found in this link https://github.com/Lexer04/Samurai-Shodown-with-Reinforcement-Learning-PPO.

• 대한물리의학회지
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• 제13권3호
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• pp.141-150
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• 2018

PURPOSE: This study was conducted to understand the adaptive responses of different modes of physical exercises utilizing skeletal muscle and the comprehensive relevance of AMPK signaling that can be activated by physical exercise as a potential molecular target in human health problems such as neuromuscular disorders (NMDs). METHODS: Most of the contents in this review article are based on recent publications concerning the main topics of interest. The reference literatures cited were obtained by basic searches of overseas academic databases such as PubMed and ScienceDirect using EndNote X7.8. RESULTS: The phenotypic adaptive responses of skeletal muscle during endurance- and resistance-based exercise training (ET and RT respectively) appear to be distinct. To explain the adaptive responses in each single mode of exercises (ET, RT) along with combined exercise training (CT), AMPK signaling is proposed as an important molecular link among those differential modes of exercise and a promising molecular target of NMDs. CONCLUSION: Based on the available evidence, intracellular AMPK signaling activated by diverse stimuli including physical exercise can be a potential and promising therapeutic target for the prevention, amelioration or cure of various human health problems including NMDs and may also be beneficial for physical rehabilitation and emergency situations that may elicit acute metabolic stresses.

• 산업경영시스템학회지
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• 제37권4호
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• pp.212-217
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• 2014

Recently, Korea Air Force has been facing a lot of problems in its pilot training system such as training time shortage due to the expensive gas price, noise pollution and difficulties in finding airspace for training. To tackle these problems, a new training system (called L-V training system) using both aircraft and its simulator has been suggested. In the system, a data link is established between aircraft and simulator to exchange their flight information. Using the flight information of simulator, aircraft can perform various air missions with or against imaginary aircraft (i.e., simulator). For this system, it is crucially important that fair fighting condition has to be guaranteed between aircraft and simulator. In this paper, we suggested an approach to impose a maneuvering restriction to simulator in order to provide fair fighting condition between aircraft and simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.